secure-local-mcp
Enables Ollama to interact with local notes through MCP tools for listing, reading, searching, and writing notes.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@secure-local-mcpsearch notes for meeting agenda"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Secure Local MCP Agent (Engineering Edition)
A Software Engineer AI Agent system that is 100% offline, secure, and directly interacts with your personal computer via the MCP (Model Context Protocol).
🎯 The Problem Solved
Current Cloud AIs pose a risk of source code data leaks and cannot directly interact with your local operating system.
This project builds a personal AI running 100% offline (Native) on Windows, capable of reading/analyzing your project's source code, as well as executing real system commands (like ping, ipconfig, dir) without being restricted by virtualization layers (Docker).
Related MCP server: Lexomni MCP
🏗️ System Architecture (Native Mode)
my_notes/ (Notes) & project_context/ (Source Code)
│
▼
src/indexer.py ──── SQLite FTS5 ──── Scan & Index Code/Text
│
▼
src/server.py ───── FastMCP ──────── 5 Tools (list, read, search, write, execute_command)
│
▼ (stdio / JSON-RPC)
src/ui.py ───────── Streamlit ────── Visual Web Interface (Transparent Tool execution flow)
│
▼
Ollama (Gemma4/Qwen) / Any Local LLM✨ Highlight Features
Feature | Details |
Codebase Indexing | SQLite FTS5 reads and indexes a variety of programming languages ( |
Native OS Commands | Allows the AI to execute Terminal (Powershell/CMD) commands on the actual Windows machine to query the network or system. |
Transparent Web UI | Every tool execution (reading files, running network commands) is displayed in detail as an Expander block, hiding nothing. |
100% Offline & Un-sandboxed | No Docker is used to avoid network isolation. Data never leaves your machine. |
Directory Traversal Protection | Blocks payloads like |
🚀 Installation & Usage (1-Click)
The system is designed to run directly on Windows (Native) to fully utilize the operating system's capabilities and permissions.
Requirements:
Python 3.10+ installed (with PATH configured).
Ollama installed and running on the default port (
http://localhost:11434).
How to run:
Simply double-click the start.bat file.
The script will automatically:
Create a virtual environment (venv).
Install the necessary dependencies (
pip install).Open the Web UI app (Streamlit) in your browser at
http://localhost:8501.
🛡️ Security Mechanisms
The system applies a robust protection layer against Directory Traversal Attacks (CWE-22):
It utilizes resolve() and is_relative_to() to ensure that the read/write paths absolutely cannot escape the 2 permitted root directories (my_notes and project_context).
📁 Project Structure
secure-local-mcp/
├── my_notes/ # Personal notes repo (.md, .txt)
├── project_context/ # Project source code for AI analysis (.py, .js, .json,...)
├── src/
│ ├── server.py # FastMCP Server (Tool declarations)
│ ├── indexer.py # SQLite FTS5 Indexing Engine (Handles Text & Code)
│ └── ui.py # Streamlit Web Chat Interface
├── start.bat # Windows (Native) automated startup script
├── requirements.txt
└── README.mdThis server cannot be deployed
Maintenance
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